Brittany Rife Magalis

This study evaluates the effectiveness of biosecurity screening tools against AI-generated synthetic homologs of proteins of concern, finding some tools can detect fragments as short as 50 nucleotides.

DeepDynaForecast uses phylogenetic trees and graph deep learning to predict epidemic transmission dynamics, showing accuracy in simulated and real HIV data.

The paper introduces DeepDynaTree, a phylogenetic-informed graph deep learning model to classify dynamic transmission clusters in infectious disease epidemics, achieving higher accuracy than existing methods.

The paper uses single-cell DNA sequencing to show that defective HIV genomes contribute to phylogenetic inference of reservoir dynamics in an animal model.

TARDiS optimizes viral genome subsampling by balancing genetic diversity and temporal distribution to improve phylogenetic analysis.

DYNAMITE identifies dynamic transmission clusters in viral phylogenies by analyzing branches rather than clades, outperforming existing tools in simulated outbreaks.

This study analyzes how global and regional public health interventions affected SARS-CoV-2 transmission clusters using genetic sequence data and phylogenetic analysis.

Contrast-FEL identifies sites with different selective pressures across multiple branches in phylogenetic trees, showing high power and low false positives.

This study shows that HIV-1 evolves differently in monocytes compared to T cells, suggesting monocytes may be a significant viral reservoir.